A Prospective Study on the Value of Ultrasound Microflow Assessment to Distinguish Malignant from Benign Solid Breast Masses: Association between Ultrasound Parameters and Histologic Microvessel Densities

Prediction of disease-free survival using strain elastography and diffuse optical tomography in patients with T1 breast cancer: a 10-year follow-up study

BACKGROUND

Early-stage breast cancer (BC) presents a certain risk of recurrence, leading to variable prognoses and complicating individualized management. Yet, preoperative noninvasive tools for accurate prediction of disease-free survival (DFS) are lacking. This study assessed the potential of strain elastography (SE) and diffuse optical tomography (DOT) for non-invasive preoperative prediction of recurrence in T1 BC and developed a prediction model for estimating the probability of DFS.

METHODS

A total of 565 eligible patients with T1 invasive BC were enrolled prospectively and followed to investigate the recurrence. The associations between imaging features and DFS were evaluated and a best-prediction model for DFS was developed and validated.

RESULTS

During the median follow-up period of 10.8 years, 77 patients (13.6%) developed recurrences. The fully adjusted Cox proportional hazards model showed a significant trend between an increasing strain ratio (SR) (P < 0.001 for trend) and the total hemoglobin concentration (TTHC) (P = 0.001 for trend) and DFS. In the subgroup analysis, an intensified association between SR and DFS was observed among women who were progesterone receptor (PR)-positive, lower Ki-67 expression, HER2 negative, and without adjuvant chemotherapy and without Herceptin treatment (all P < 0.05 for interaction). Significant interactions between TTHC status and the lymphovascular invasion, estrogen receptor (ER) status, PR status, HER2 status, and Herceptin treatment were found for DFS(P < 0.05).The imaging-clinical combined model (TTHC + SR + clinicopathological variables) proved to be the best prediction model (AUC = 0.829, 95% CI = 0.786-0.872) and was identified as a potential risk stratification tool to discriminate the risk probability of recurrence.

CONCLUSION

The combined imaging-clinical model we developed outperformed traditional clinical prognostic indicators, providing a non-invasive, reliable tool for preoperative DFS risk stratification and personalized therapeutic strategies in T1 BC. These findings underscore the importance of integrating advanced imaging techniques into clinical practice and offer support for future research to validate and expand on these predictive methodologies.

Current status and future perspectives of contrast-enhanced ultrasound diagnosis of breast lesions

Advances in various imaging modalities for breast lesions have improved diagnostic capabilities not only for tumors but also for non-tumorous lesions. Contrast-enhanced ultrasound (CEUS) plays a crucial role not only in the differential diagnosis of breast lesions, identification of sentinel lymph nodes, and diagnosis of lymph node metastasis but also in assessing the therapeutic effects of neoadjuvant chemotherapy (NAC). In CEUS, two image interpretation approaches, i.e., qualitative analysis and quantitative analysis, are employed and applied in various clinical settings. In this paper, we review CEUS for breast lesions, including its various applications.

Artificial intelligence for ultrasound microflow imaging in breast cancer diagnosis

PURPOSE

To develop and evaluate artificial intelligence (AI) algorithms for ultrasound (US) microflow imaging (MFI) in breast cancer diagnosis.

MATERIALS AND METHODS

We retrospectively collected a dataset consisting of 516 breast lesions (364 benign and 152 malignant) in 471 women who underwent B-mode US and MFI. The internal dataset was split into training (n = 410) and test datasets (n = 106) for developing AI algorithms from deep convolutional neural networks from MFI. AI algorithms were trained to provide malignancy risk (0-100%). The developed AI algorithms were further validated with an independent external dataset of 264 lesions (229 benign and 35 malignant). The diagnostic performance of B-mode US, AI algorithms, or their combinations was evaluated by calculating the area under the receiver operating characteristic curve (AUROC).

RESULTS

The AUROC of the developed three AI algorithms (0.955-0.966) was higher than that of B-mode US (0.842, P < 0.0001). The AUROC of the AI algorithms on the external validation dataset (0.892-0.920) was similar to that of the test dataset. Among the AI algorithms, no significant difference was found in all performance metrics combined with or without B-mode US. Combined B-mode US and AI algorithms had a higher AUROC (0.963-0.972) than that of B-mode US (P < 0.0001). Combining B-mode US and AI algorithms significantly decreased the false-positive rate of BI-RADS category 4A lesions from 87% to 13% (P < 0.0001).

CONCLUSION

AI-based MFI diagnosed breast cancers with better performance than B-mode US, eliminating 74% of false-positive diagnoses in BI-RADS category 4A lesions.

Clinical application of intraoperative ultrasound superb microvascular imaging in brain tumors resections: contributing to the achievement of total tumoral resection

BACKGROUND

To investigate whether the intraoperative superb microvascular imaging(SMI) technique helps evaluate lesion boundaries compared with conventional grayscale ultrasound in brain tumor surgery and to explore factors that may be associated with complete radiographic resection.

METHODS

This study enrolled 57 consecutive brain tumor patients undergoing surgery. During the operation, B-mode and SMI ultrasound evaluated the boundaries of brain tumors. MRI before and within 48h after surgery was used as the gold standard to evaluate gross-total resection(GTR). The ultrasound findings and GTR results were analyzed to determine the imaging factors related to GTR.

RESULTS

A total of 57 patients were enrolled in the study, including 32 males and 25 females, with an average age of 53.4 ± 14.1 years old(range 19 ~ 80). According to the assessment criteria of MRI, before and within 48 h after the operation, 37(63.9%) cases were classified as GTR, and 20(35.1%) cases were classified as GTR. In comparing tumor interface definition between B-mode and SMI mode, SMI improved HGG boundary recognition in 5 cases(P = 0.033). The results showed that the tumor size ≥ 5 cm and unclear ultrasonic boundary were independent risk factors for nGTR (OR>1, P<0.05).

CONCLUSIONS

As an innovative intraoperative doppler technique in neurosurgery, SMI can effectively demarcate the tumor's boundary and help achieve GTR as much as possible.

Value of Contrast-Enhanced Microflow Imaging in Diagnosis of Breast Masses in Comparison with Contrast-Enhanced Ultrasound

RATIONALE AND OBJECTIVES

To investigate the value of contrast-enhanced microflow imaging (CEUS-MFI) in distinguishing benign and malignant breast masses.

METHODS

A total of 116 breast masses classified as Breast Imaging Reporting and Data System (BI-RADS) category 3-5 by ultrasound (US) were included. Both contrast-enhanced ultrasound (CEUS) and CEUS-MFI were performed before excision or biopsy, with features and diagnostic efficiency analyzed. The US and CEUS BI-RADS 4A masses were also re-assessed by CEUS-MFI.

RESULTS

The features of CEUS-MFI including both interior and peripheral enlarged, twisted vessels (both P < 0.05), penetrating vessels (P = 0.007), and radial/spiculated vessels (P < 0.001) were more frequently detected in malignant masses, while peripheral annular vessels were mostly observed in benign masses (P < 0.001). Interestingly, a significant difference in the orientation of penetrating vessels between benign and malignant masses was found (P < 0.001), with parallel orientation mostly displayed in benign masses, while vertical or multiple-direction orientation mostly displayed in malignant masses. The microvascular architecture of breast masses was categorized into five patterns: avascular, line-like, tree-like, root hair-like, and crab claw-like pattern. Benign masses mainly displayed tree-like pattern (77.1% vs 10.9%, P < 0.05); malignant masses mainly displayed root hair-like (34.8% vs 5.7%, P < 0.05) and crab claw-like patterns (50.0% vs 1.4%, P < 0.05). The diagnostic efficiency of CEUS-MFI was higher relative to CEUS and US. In addition, CEUS-MFI decreased the biopsy rates of US and CEUS BI-RADS 4A masses without missing malignancies.

CONCLUSION

CEUS-MFI could be a valuable and promising technique in diagnosis of breast masses, and could provide more diagnostic information for radiologists.

Preoperative Role of Superb Microvascular Imaging and Shear-Wave Elastography for Prediction of Axillary Lymph Node Metastasis in Patients With Breast Cancer

ABSTRACT

This study aims to evaluate the role of shearwave elastography (SWE) and superb microvascular imaging (SMI) for preoperative prediction of axillary lymph node metastasis (ALNM) in patients with breast cancer. In a cohort of 214 women with breast cancer, B-Mode ultrasonography (US), SMIvascular-index (SMIvi), and SWE (E-mean, E-ratio) values were recorded before tru-cut biopsy. Axillary fine-needle aspiration biopsy (FNAB) and sentinel lymph node sampling results were collected. Imaging findings and histopathological data were statistically compared. Receiver operating characteristic curve analysis was used to evaluate diagnostic performance. Reverse stepwise logistical regression analysis was conducted. Although ALNM was negative in 111 cases, it was positive in 103 patients. Axillary lymph node metastasis (+) group had larger size ( P < 0.001), higher vascularization (SMIvi: 8.0 ± 6.0 versus 5.0 ± 4.3, P < 0.001), and higher elasticity value (E-mean: 129 ± 31 kPa versus 117.3 ± 40 kPa, P = 0.014). Axillary lymph node metastasis was observed statistically more frequently in Her-2 positive cases ( P = 0.005). There was no significant difference between other B-mode US findings ( P > 0.05), SMI Adler ( P = 0.878), and E-ratio ( P = 0.212). The most appropriate cutoff value for the prediction of ALNM was 23.5 mm for size, 3.8 for SMIvi, and 138.5 kPa for E-mean. The most sensitive (77%) method was the SMIvi measurement, while the most specific (86%) finding was Her-2 positivity. The combined model (being Her-2 positive, >23.5 cm, and >3.8 SMIvi) increased the specificity (78%), PPV (71%), and accuracy (68%). Although the increased size is a previously studied parameter in predicting the risk of ALNM, Her-2 and data obtained by SWE, and SMI can be used to assist conventional US.

Evaluating diagnostic significance: The utilization of elastography and contrast-enhanced ultrasound for differential diagnosis in breast lesions

OBJECTIVE

The primary aim of this study is to assess the diagnostic efficacy of elastography and contrast-enhanced ultrasound (CEUS) in the identification of breast lesions subsequent to the optimization and correction of the BI-RADS category 4 classification obtained through conventional ultrasound. The objective is to augment both the specificity and accuracy of breast lesion diagnosis, thereby establishing a reliable framework for reducing unnecessary biopsies in clinical settings.

METHODS

A cohort comprising 50 cases of breast lesions classified under BI-RADS category 4 was collected during the period from November 2022 and November 2023. These cases were examined utilizing strain elastography (SE), shear wave elastography (SWE), and CEUS. Novel scoring methodologies for ultrasonic elastography (UE) and CEUS were formulated for this investigation. Subsequently, the developed UE and CEUS scoring systems were used to refine and optimize the conventional BI-RADS classification, either in isolation or in conjunction. Based on the revised classification, the benign group was classified as category 3 and the suspected malignant group was classified as category 4a and above, with pathological results serving as the definitive reference standard. The diagnostic efficacy of the optimized UE and CEUS, both independently and in combination, was meticulously scrutinized and compared using receiver operating characteristic (ROC) curve analysis, with pathological findings as the reference standard.

RESULTS

Within the study group, malignancy manifested in 11 cases. Prior to the implementation of the optimization criteria, 78% (39 out of 50) of patients underwent biopsies deemed unnecessary. Following the application of optimization criteria, specifically a threshold of≥8.5 points for the UE scoring method and≥6.5 points for the CEUS scoring method, the incidence of unnecessary biopsies diminished significantly. Reduction rates were observed at 53.8% (21 out of 39) with the UE protocol, 56.4% (22 out of 39) with the CEUS protocol, and 89.7% (35 out of 39) with the combined UE and CEUS optimization protocols.

CONCLUSION

The diagnostic efficacy of conventional ultrasound BI-RADS category 4 classification for breast lesions is enhanced following optimized correction using UE and CEUS, either independently or in conjunction. The application of the combined protocol demonstrates a notable reduction in the incidence of unnecessary biopsies.

Value of micro-flow imaging and high-definition micro-flow imaging in differentiating malignant and benign breast lesions

AIM

To evaluate the value of non-contrast micro-flow imaging (MFI) and high-definition micro-flow imaging (HD-MFI) in differentiating malignant and benign breast lesions.

MATERIALS AND METHODS

One hundred and thirty-three patients with 138 breast lesions (80 benign and 58 malignant lesions) were examined using colour Doppler flow imaging (CDFI), MFI, and HD-MFI before biopsy, with blood flow signals graded into four types (grade 0, 1, 2, and 3) and penetrating vessels evaluated. The micro-vascular patterns of MFI and HD-MFI were evaluated and classified into five patterns: avascular, line-like, tree-like, root hair-like, and crab claw-like pattern. The diagnostic efficiency of micro-vascular patterns was analysed. Moreover, ultrasound Breast Imaging Reporting and Data System (BI-RADS) 4A lesions were also re-assessed according to the micro-vascular patterns of MFI or HD-MFI.

RESULTS

The capability of detecting blood flow and penetrating vessels from high to low was HD-MFI, MFI, and CDFI, respectively (p<0.05). Rich blood flow signals, penetrating vessels, and root hair-like or crab claw-like pattern were more likely in malignant breast lesions, while few blood flow signals, tree-like pattern were mostly in benign lesions (p<0.05). The diagnostic efficiency of HD-MFI and MFI were higher than CDFI (p>0.05). MFI could reduce unnecessary biopsy of 52 US BI-RADS 4A lesions but with two malignancies missed, while 56 ultrasound BI-RADS 4A lesions could be downgraded by HD-MFI with none malignancies missed.

CONCLUSIONS

MFI and HD-MFI can detect more blood flow in breast lesions than CDFI, and could help distinguish benign and malignant breast lesions. HD-MFI could reduce the unnecessary biopsy of US BI-RADS 4A lesions without missed malignancy.

Ultrasound Microvessel Visualization in Cervical Cancer: Association Between Novel Ultrasound Techniques and Histologic Microvessel Densities

OBJECTIVE

The aim of the work described here was to evaluate the feasibility of superb microvascular imaging (SMI) and vascular endothelial growth factor receptor 2 (VEGFR2)-targeted microbubble (MBVEGFR2)-based ultrasound molecular imaging (USMI) for visualizing microvessels in cervical cancer.

METHODS

Hela cells were used to establish subcutaneous cervical cancer models. SMI and MBVEGFR2-based USMI were performed, and the results were compared with intratumoral microvessel density (MVD) in four groups based on tumor diameter (<3 mm, 3-5 mm, 5-7 mm and ≥7 mm). The vascularization index (VI, %) was evaluated for SMI, and the normalized intensity difference (NID) for USMI.

RESULTS

Tumors with diameters ranging from 3 to 5 mm had the highest VI (39.07 ± 1.58) in SMI, and VI significantly decreased with increasing tumor size (all p values <0.001). The strongest signal intensity was observed in very early tumors (d < 3 mm: 43.80 ± 3.58%) after MBVEGFR2 administration; the NID gradually decreased with increasing diameter of tumors (all p values = 0.007). However, no significant differences were observed in NID after administration of non-targeted (control) microbubbles (MBCon) (all p values = 0.125). MBVEGFR2-based USMI had the strongest correlation with MVD in displaying microvessels of cervical cancer compared with SMI and MBCon (R2 = 0.78 vs. R2 = 0.40 and R2 = 0.38).

CONCLUSION

These findings validate the superiority and accuracy of MBVEGFR2-based USMI for microvessel imaging and monitoring of angiogenesis in cervical cancer compared with SMI and MBCon. Nonetheless, SMI remains an alternative to microvessel imaging when ultrasonic contrast agent use is contraindicated.

The kinetic quantitative characteristics of non-mass breast lesions with contrast-enhanced ultrasound: a prospective study

OBJECTIVE

To characterize non-mass breast lesions (NML) quantitatively by contrast-enhanced ultrasound (CEUS) and to evaluate its additional diagnostic value based on the Breast Imaging Reporting and Data System (BI-RADS) categories.

METHODS

A prospective study was performed among consecutive patients with NMLs. All lesions were examined by grayscale ultrasound and CEUS and diagnosed on pathology. Standard mammograms were obtained in the patients over 30 years old. Three independent radiologists assessed the features on grayscale ultrasound and mammograms and classified NMLs according to BI-RADS categories. Combined with the quantitative analysis in CEUS, the BI-RADS categories were reassessed, and the sensitivity, specificity, positive-predictive value, negative-predictive value and area under the receiver operating characteristic curve (AUC) were calculated for the evaluation of the diagnostic performance.

RESULTS

30 benign and 24 malignant NMLs were finally enrolled in this study, with ductal carcinoma in situ being the majority of malignant (15/24). Average contrast signal intensity (AI), wash-in rate (WiR) and enhancement intensity at 40 s (I40) were found to be the most efficient kinetic parameters to diagnose malignant NMLs. Combined with the cut-off values of 205.2 for AI, 127.8 for WiR and 136.4 for I40, the diagnostic accuracy was improved (AUC = 0.904), with the sensitivity of 95.8% and the specificity of 70.0%.

CONCLUSION

The results suggested that hyperenhancement and rapid wash-in and wash-out are the characteristics of malignant NMLs. The kinetic analysis using CEUS can reflect hypervascular nature of malignant NMLs, thus improving the diagnostic performance combined with grayscale ultrasound.

ADVANCES IN KNOWLEDGE

In this study, we quantified the enhancement characteristics of non-mass breast lesions with CEUS. We revealed that the combination of CEUS and conventional ultrasound provided higher sensitivity for diagnosing malignant NMLs.

Maximum intensity projection based on high frame rate contrast-enhanced ultrasound for the differentiation of breast tumors

Objective

We explored the role of maximum intensity projection (MIP) based on high frame rate contrast-enhanced ultrasound (H-CEUS) for the differentiation of breast tumors.

Methods

MIP imaging was performed in patients with breast tumors who underwent H-CEUS examinations. The microvasculature morphology of breast tumors was assessed. The receiver operating characteristic curve was plotted to evaluate the diagnostic performance of MIP.

Results

Forty-three breast tumors were finally analyzed, consisting of 19 benign and 24 malignant tumors. For the ≤30-s and >30-s phases, dot-, line-, or branch-like patterns were significantly more common in benign tumors. A tree-like pattern was only present in the benign tumors. A crab claw-like pattern was significantly more common in the malignant tumors. Among the tumors with crab claw-like patterns, three cases of malignant tumors had multiple parallel small spiculated vessels. There were significant differences in the microvasculature morphology for the ≤30-s and >30-s phases between the benign and malignant tumors (all p < 0.001). The area under the curve, sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the ≤30-s phase were all higher than those of the >30-s phase for the classification of breast tumors.

Conclusion

MIP based on H-CEUS can be used for the differentiation of breast tumors, and the ≤30-s phase had a better diagnostic value. Multiple parallel small spiculated vessels were a new finding, which could provide new insight for the subsequent study of breast tumors.

Novel model based on ultrasound predict axillary lymph node metastasis in breast cancer

BACKGROUND

Whether there is axillary lymph node metastasis is crucial for formulating the treatment plan for breast cancer. Currently, invasive methods are still used for preoperative evaluation of lymph nodes. If non-invasive preoperative evaluation can be achieved, it will effectively improve the treatment plan.

OBJECTIVE

Constructed a predict model based on ultrasound examination, which forest axillary lymph node metastasis in breast cancer, and validated this model.

METHOD

Patients admitted to Xiamen First Hospital from April 2018 to August 2021 with complete case data were included in this study. Patients who had undergone breast cancer resection and axillary lymph node dissection or sentinel lymph node biopsy were divided into a training and validation cohort in a 7:3 ratio. In the training cohort, patients were divided into metastatic and non-metastatic groups based on whether axillary lymph nodes had metastasis. The parameters of the two groups were compared, and statistically significant parameters were included in multivariate analysis. Then, a Nomogram model was constructed, named Lymph metastasis predict model (LMPM). Calibration curves, receiver operating curve (ROC), and decision curve analysis (DCA) were plotted between the training and validation cohort, calculate the risk score of each patient, identify the optimal cutoff value, and test the predictive efficacy of LMPM.

RESULT

Two hundred seventy-three patients were enrolled in final study, the average age 49.7 ± 8.7, training cohort included 191 patients, the diameter of breast cancer, the lymph node peak systolic flow velocity (LNPS) and the cortex area hilum ratio (CH) of lymph node were exist significant difference in metastatic and non-metastatic group. Multivariate analysis showed cancer diameter, LNPS and CH included in LMPM, the cutoff value was 95, the calibration curve, ROC, DCA in training and validation cohort show satisfactory result.

CONCLUSION

The predict model-LMPM, can predict axillary lymph node metastasis in breast cancer, which is useful for developing personalized treatment plans. However, further validation of the model is required by incorporating a larger number of patients.

Superb Microvascular Imaging for the Differentiation of Benign and Malignant Breast Lesions: A System Review and Meta-Analysis

OBJECTIVE

To evaluate the diagnostic performance of SMI in the diagnosis of benign and malignant breast lesions.

METHODS

A systematic search of PubMed, EMBASE, Cochrane, OVID, SCI, and SCOPUS was performed to find relevant studies which applied SMI to differentiate benign and malignant breast lesions. All the studies were published before October 10, 2022. Only studies published in English were collected. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was applied to assess the quality of the included studies. Summary receiver operating characteristic (SROC) modeling was also performed to the diagnostic performance of SMI in the diagnosis of benign and malignant breast lesions. Subgroup analyses and meta-regression were performed to find out the heterogeneity.

RESULTS

Twenty studies which include a total of 2873 lesions (1748 benign and 1125 malignant) in 2740 patients were evaluated in this meta-analysis. The summary sensitivity and specificity were 0.82 (95% confidence interval [CI]: 0.76-0.86), 0.70 (95% CI: 0.64-0.76) for SMI vascular degree, 0.77 (95% CI: 0.67-0.84), 0.79 (95% CI: 0.75-0.83) for SMI vascular distribution, 0.78 (95% CI: 0.70-0.84), 0.75 (95% CI: 0.69-0.80) for SMI vascular morphology, 0.81 (95% CI: 0.72-0.87), 0.80 (95% CI: 0.75-0.85) SMI penetration vessel. For SMI overall vascular features, the summary sensitivity and summary specificity were 0.74 (95% CI: 0.61-0.84) and 0.80 (95% CI: 0.76-0.84). The result of subgroup analysis and meta-analysis showed malignant rate and country might be the cause of heterogeneity of diagnostic accuracy of vascular grade and morphology.

CONCLUSION

SMI vascular features have high sensitivity and specificity in the differentiation of benign and malignant lesions. Future international multicenter studies in various regions with large sample size are required to confirm these findings.

Association between vascular ultrasound features and DNA sequencing in breast cancer: a preliminary study

There are few radiogenomic studies to correlate ultrasound features of breast cancer with genomic changes. We investigated whether vascular ultrasound phenotypes are associated with breast cancer gene profiles for predicting angiogenesis and prognosis. We prospectively correlated quantitative and qualitative features of microvascular ultrasound (vascular index, vessel morphology, distribution, and penetrating vessel) and contrast-enhanced ultrasound (time-intensity curve parameters and enhancement pattern) with genomic characteristics in 31 breast cancers. DNA obtained from breast tumors and normal tissues were analyzed using targeted next-generation sequencing of 105 genes. The single-variant association test was used to identify correlations between vascular ultrasound features and genomic profiles. Chi-square analysis was used to detect single nucleotide polymorphisms (SNPs) associated with ultrasound features by estimating p values and odds ratios (ORs). Eight ultrasound features were significantly associated with 9 SNPs (p < 0.05). Among them, four ultrasound features were positively associated with 5 SNPs: high vascular index with rs1136201 in ERBB2 (p = 0.04, OR = 7.75); large area under the curve on contrast-enhanced ultrasound with rs35597368 in PDGFRA (p = 0.04, OR = 4.07); high peak intensity with rs35597368 in PDGFRA (p = 0.049, OR = 4.05) and rs2305948 in KDR (p = 0.04, OR = 5.10); and long mean transit time with rs2275237 in ARNT (p = 0.02, OR = 10.25) and rs755793 in FGFR2 (p = 0.02, OR = 10.25). We identified 198 non-silent SNPs in 71 various cancer-related genes. Vascular ultrasound features can reflect genomic changes associated with angiogenesis and prognosis in breast cancer.

Utility of ultrasound Angio-PLUS imaging for detecting blood flow in breast masses and comparison with color Doppler for differentiating benign from malignant masses

BACKGROUND

Tumor neo-angiogenesis plays an important role in the development and growth of breast cancers, but its detection by imaging is challenging. A novel microvascular imaging (MVI) technique, Angio-PLUS, promises to overcome the limitations of color Doppler (CD) in detecting low-velocity flow and small diameter vessels.

PURPOSE

To determine the utility of the Angio-PLUS technique for detecting blood flow in breast masses and compare it with CD for differentiating benign from malignant masses.

MATERIAL AND METHODS

A total of 79 consecutive women with breast masses were prospectively evaluated using CD and Angio-PLUS techniques, and biopsied as per BI-RADS recommendations. Vascular imaging scores were assigned using three factors (number, morphology, and distribution) and vascular patterns were divided into five groups: internal-dot-spot, external-dot-spot, marginal, radial, and mesh patterns. The independent samples t-test, Mann-Whitney U test, Wilcoxon signed rank test, or Fisher's exact test were used to compare the two groups as appropriate. Area under the receiver operating characteristic (ROC) curve (AUC) methods were used to assess diagnostic accuracy.

RESULTS

Vascular scores were significantly higher on Angio-PLUS than CD (median=11, [IQR=9-13] vs. 5 [IQR=3-9], P < 0.001). Malignant masses had higher vascular scores than benign masses on Angio-PLUS (P < 0.001). AUC was 80% (95% CI=70.3-89.7; P < 0.001) for Angio-PLUS and 51.9% for CD. Using Angio-PLUS at a cutoff value of ≥9.5, sensitivity was 80% and specificity was 66.7%. Vascular pattern descriptors on AP showed good correlation with histopathological results (PPV mesh 95.5%, radial 96.9%, and NPV of marginal orientation 90.5%).

CONCLUSION

Angio-PLUS was more sensitive in detecting vascularity and superior in differentiating benign from malignant masses compared to CD. Vascular pattern descriptors on Angio-PLUS were useful.

Recent Advances in Ultrasound Breast Imaging: From Industry to Clinical Practice

Breast ultrasound (US) has undergone dramatic technological improvement through recent decades, moving from a low spatial resolution, grayscale-limited technique to a highly performing, multiparametric modality. In this review, we first focus on the spectrum of technical tools that have become commercially available, including new microvasculature imaging modalities, high-frequency transducers, extended field-of-view scanning, elastography, contrast-enhanced US, MicroPure, 3D US, automated US, S-Detect, nomograms, images fusion, and virtual navigation. In the subsequent section, we discuss the broadened current application of US in breast clinical scenarios, distinguishing among primary US, complementary US, and second-look US. Finally, we mention the still ongoing limitations and the challenging aspects of breast US.

Use of new microcirculation software allows the demonstration of dermis vascularization

AIMS

Current ultrasound (US) Doppler techniques cannot demonstrate the vascularization of the dermis. The purpose of this study was to investigate whether the new Superb Vascular Imaging (SMI) and Microvascular Flow (MV-Flow) techniques improve the detection of normal dermis vessels. SMI and MV-Flow were compared side-by-side to conventional power-Doppler (PD) imaging.

METHODS

By using US, 50 healthy volunteers were evaluated at level of five body areas: forehead, forearm, palm, buttock, and thigh. Two off-site operators evaluated the images to assess the difference between SMI and PD imaging and between MV-Flow and PD imaging in terms of dermis flow amount. A 0-3 scoring system was adopted.

RESULTS

SMI scored grade 0 in 0% of body areas, grade 1 in 58%, grade 2 in 33%, and grade 3 in 9%. In comparison with SMI, PD scored grade 0 in 38% of body areas, grade 1 in 56%, grade 2 in 6%, and grade 3 in 0%. MV-Flow scored grade 0 in 0% of body areas, grade 1 in 52%, grade 2 in 43%, and grade 3 in 6%. Comparted to MV-Flow, PD scored grade 0 in 53% of body areas, grade 1 in 34%, grade 2 in 13%, and grade 3 in 0%. The difference in terms of sensitivity was statistically significant for all the body areas investigated.

CONCLUSIONS

We found both SMI and MV-Flow to be superior to PD imaging and capable to demonstrate normal vascularization of the dermis.

Comparison of microvascular flow imaging and contrast-enhanced ultrasound for blood flow analysis of cervical lymph node lesions

OBJECTIVE

To compare the diagnostic value of microvascular flow imaging (MVFI) with that of contrast-enhanced ultrasound (CEUS) for the analysis of blood flow in benign and malignant cervical lymph nodes.

MATERIAL AND METHODS

As a prospective study, 95 cervical enlarged lymph nodes (43 benign and 52 malignant) were observed in 95 patients using conventional ultrasonography (including gray and Color Doppler Flow Imaging), CEUS, and MVFI. Two researchers evaluated vascular parameters of MVFI (vascular distribution, internal vascular features, vascular index) and CEUS (enhancement mode, enhancement type) and compared the diagnostic effects of MVFI and CEUS.All results were compared with pathological findings.

RESULTS

There were significant differences in the vascular distribution and internal vascular features of benign and malignant lymph nodes on MVFI (P < 0.05). The vascular distribution of benign lymph nodes was mainly of the central and avascular types, the internal blood vessels were mostly normal, the vascular distribution of malignant lymph nodes was mainly mixed, the internal vessels were mainly tortuous and displaced. The optimal cut-off value of the benign and malignant lymph node vascular index (VI) was 15.55%, and the area under the receiver operating characteristic curve (AUC) of the VI was 0.876. There were also significant differences in the enhancement mode and types of benign and malignant lymph nodes in CEUS (P < 0.05). The benign lymph nodes showed centrifugal perfusion, and the enhancement types were mostly type I and type II. Most malignant lymph nodes showed centripetal or mixed perfusion, and the enhancement types were usually type III and type IV. The accuracy, sensitivity, and specificity of CEUS in the diagnosis of lymph node lesions were 84.2%, 84.6% and 83.7%, respectively, and the AUC was 0.845. The accuracy, sensitivity, and specificity of MVFI in the diagnosis of lymph node lesions were 85.3%, 84.6%, and 86.0%, respectively, and the AUC was 0.886.

CONCLUSION

Both CEUS and MVFI are valuable in differentiating benign and malignant lesions of lymph nodes and have a similar diagnostic performance; however, MVFI is less invasive and simpler than CEUS. Therefore it is preferred for auxiliary examination of enlarged lymph nodes that are difficult to diagnose by conventional ultrasound.

Diagnostic accuracy of contrast-enhanced ultrasound synchronized with shear wave elastography in the differential diagnosis of benign and malignant breast lesions: a diagnostic test

Background

Breast cancer (BC) is one of the most common malignancies affecting women. Timely and accurate diagnosis is crucial for treatment and prognosis. Some studies have found that elastography combined with microperfusion characteristics, which are mostly described by contrast-enhanced ultrasound (CEUS), could help in the diagnosis of breast lesions. This study aimed to assess the diagnostic performance of CEUS synchronized with shear wave elastography (SWE) in discriminating between benign and malignant breast lesions by using real-time contrast elastography images to analyze shell elasticity and contrast intensity.

Methods

A total of 26 pathologically confirmed breast lesions in 26 patients were retrospectively reviewed. Each patient underwent conventional B-mode ultrasound, CEUS, and then SWE data was obtained from a frame of image that was almost identical to the B-mode and CEUS images when acquiring time to peak (TTP). Breast lesions were evaluated based on the Breast Imaging Reporting and Data System (BI-RADS) and quantitative characteristics that describe the stiffness and intensity of contrast of the 1.0-3.0 mm shell region. Quantitative aspects of the inner lesions and shell on the elastogram included the maximum (Emax), mean (Emean), and minimum (Emin) Young's moduli. Quantitative enhanced features included maximum (Imax) and mean (Imean) intensity. We took postoperative pathological results as the gold standard. Receiver operating characteristic (ROC) curves were used to compare the diagnostic efficacy of the 2 examination modalities, either alone or in combination.

Results

The age of the patients ranged from 23 to 76 years, with a 42.5-year average age. In all breast lesions, 19 were benign and 7 were malignant. SWE synchronized with CEUS can effectively improve the diagnostic performance of breast lesions, and Emean + Imean and Emax + Emean + Imean of shell at 1.0 mm both had the highest area under the curve (AUC) of 0.86 [95% confidence interval (CI): 0.67, 0.96], with the sensitivity and specificity of 71.43% and 89.47%, respectively.

Conclusions

The combination of CEUS and SWE has a better diagnostic value in differentiating benign and malignant breast lesions compared to separate techniques.

Correlations between contrast-enhanced ultrasound and microvessel density in non-small cell lung cancer: A prospective study

Background

Immunohistochemical microvessel density (MVD) is an early indicator of angiogenesis and it could be used to evaluate the therapeutic efficacy of non-small cell lung cancer (NSCLC). We sought to identify the ability of contrast-enhanced ultrasound (CEUS) in evaluating MVD of subpleural NSCLC.

Methods

We prospectively collected CEUS data of NSCLC confirmed by ultrasound-guided transthoracic needle biopsy from October 2019 to February 2021, The MVD of NSCLC counted by CD34-positive vessels of immunohistochemical staining. Microflow enhancement (MFE) of CEUS was divided into "dead wood", "cotton", and "vascular" patterns. Pathology subgroup and MVD between different MFE patterns were analyzed, respectively. The arrival time, time to peak, peak intensity (PI), and area under curve (AUC) derivefrom time-intensity curve of CEUS with MVD in NSCLC and its pathological subgroups (adenocarcinoma and squamous cell carcinoma) were subjected to correlation analysis.

Results

A total of 87 patients were included in this study, consisting of 53 cases of adenocarcinoma and 34 cases of squamous cell carcinoma with a mean MVD of 27.8 ± 12.2 mm^-1. There was a significant statistical difference in MFE patterns between two pathological subgroups (p < 0.05). Besides, the MVD of "cotton" and "vascular" patterns were significantly higher than that of "dead wood" pattern (both of p < 0.05), whereas there was no significant difference in MVD between "cotton" pattern and "vascular" pattern. PI and AUC of CEUS were positively correlated with the MVD of NSCLC (r = 0.497, p < 0.001, and r = 0.367, p < 0.001, respectively). Besides, PI and AUC of CEUS were positively correlated with the MVD of squamous cell carcinoma (r = 0.802, and r = 0.663, respectively; both of p < 0.001). Only the PI was positively correlated with the MVD of lung adenocarcinoma (r = 0.288, p = 0.037).

Conclusions

MFE patterns and quantitative parameters of CEUS had good correlation with MVD of NSCLC, especially in squamous cell carcinoma.

Multi-parameter ultrasonography-based predictive model for breast cancer diagnosis

OBJECTIVES

To develop, validate, and evaluate a predictive model for breast cancer diagnosis using conventional ultrasonography (US), shear wave elastography (SWE), and contrast-enhanced US (CEUS).

MATERIALS AND METHODS

This retrospective study included 674 patients with 674 breast lesions. The data, a main and an independent datasets, were divided into three cohorts. Cohort 1 (80% of the main dataset; n = 448) was analyzed by logistic regression analysis to identify risk factors and establish the predictive model. The area under the receiver operating characteristic curve (AUC) was analyzed in Cohort 2 (20% of the main dataset; n = 119) to validate and in Cohort 3 (the independent dataset; n = 107) to evaluate the predictive model.

RESULTS

Multivariable regression analysis revealed nine independent breast cancer risk factors, including age > 40 years; ill-defined margin, heterogeneity, rich blood flow, and abnormal axillary lymph nodes on US; enhanced area enlargement, contrast agent retention, and irregular shape on CEUS; mean SWE higher than the cutoff value (P < 0.05 for all). The diagnostic performance of the model was good, with AUC values of 0.847, 0.857, and 0.774 for Cohorts 1, 2, and 3, respectively. The model increased the diagnostic specificity (from 31% to 81.3% and 7.3% to 73.1% in cohorts 2 and 3, respectively) without a significant loss in sensitivity (from 100.0% to 90.1% and 100.0% to 81.8% in cohorts 2 and 3, respectively).

CONCLUSION

The multi-parameter US-based model showed good performance in breast cancer diagnosis, improving specificity without a significant loss in sensitivity. Using the model could reduce unnecessary biopsies and guide clinical diagnosis and treatment.

Ultrasound super-resolution imaging for differential diagnosis of breast masses

OBJECTIVE

Ultrasound imaging has been widely used in breast cancer screening. Recently, ultrasound super-resolution imaging (SRI) has shown the capability to break the diffraction limit to display microvasculature. However, the application of SRI on differential diagnosis of breast masses remains unknown. Therefore, this study aims to evaluate the feasibility and clinical value of SRI for visualizing microvasculature and differential diagnosis of breast masses.

METHODS

B mode, color-Doppler flow imaging (CDFI) and contrast-enhanced ultrasound (CEUS) images of 46 patients were collected respectively. SRI were generated by localizations of each possible contrast signals. Micro-vessel density (MVD) and microvascular flow rate (MFR) were calculated from SRI and time to peak (TTP), peak intensity (PI) and area under the curve (AUC) were obtained by quantitative analysis of CEUS images respectively. Pathological results were considered as the gold standard. Independent chi-square test and multivariate logistic regression analysis were performed using these parameters to examine the correlation.

RESULTS

The results showed that SRI technique could be successfully applied on breast masses and display microvasculature at a significantly higher resolution than the conventional CDFI and CEUS images. The results showed that the PI, AUC, MVD and MFR of malignant breast masses were significantly higher than those of benign breast masses, while TTP was significantly lower than that of benign breast masses. Among all five parameters, MVD showed the highest positive correlation with the malignancy of breast masses.

CONCLUSIONS

SRI is able to successfully display the microvasculature of breast masses. Compared with CDFI and CEUS, SRI can provide additional morphological and functional information for breast masses. MVD has a great potential in assisting the differential diagnosis of breast masses as an important imaging marker.

Diagnostic Value of Superb Microvascular Imaging in Differentiating Benign and Malignant Breast Tumors: A Systematic Review and Meta-Analysis

PURPOSE

We performed a systematic review and meta-analysis of studies that investigated the diagnostic performance of Superb Microvascular Imaging (SMI) in differentiating between benign and malignant breast tumors.

METHODS

Studies published between January 2010 and March 2022 were retrieved by online literature search conducted in PubMed, Embase, Cochrane Library, Web of Science, China Biology Medicine Disc, China National Knowledge Infrastructure, Wanfang, and Vip databases. Pooled sensitivity, specificity, and diagnostic odd ratios were calculated using Stata software 15.0. Heterogeneity among the included studies was assessed using I2 statistic and Q test. Meta-regression and subgroup analyses were conducted to investigate potential sources of heterogeneity. Influence analysis was conducted to determine the robustness of the pooled conclusions. Deeks' funnel plot asymmetry test was performed to assess publication bias. A summary receiver operating characteristic curve (SROC) was constructed.

RESULTS

Twenty-three studies involving 2749 breast lesions were included in our meta-analysis. The pooled sensitivity and specificity were 0.80 (95% confidence interval [CI], 0.77-0.84, inconsistency index [I2] = 28.32%) and 0.84 (95% CI, 0.79-0.88, I2 = 89.36%), respectively. The pooled diagnostic odds ratio was 19.95 (95% CI, 14.84-26.82). The area under the SROC (AUC) was 0.85 (95% CI, 0.81-0.87).

CONCLUSION

SMI has a relatively high sensitivity, specificity, and accuracy for differentiating between benign and malignant breast lesions. It represents a promising supplementary technique for the diagnosis of breast neoplasms.

Prospective analysis of breast masses using the combined score for quantitative ultrasonography parameters

To investigate the diagnostic value of combined SWE, SMI, and B-mode US scores for distinguishing between benign and malignant masses. A total of 450 breast masses that underwent US-guided core needle biopsies were prospectively enrolled. The breast masses were assessed based on the BI-RADS and quantitative SWE and SMI parameters. The SWEmax, SWEratio, and SMI_VI cutoff value were determined using Youden’s index by comparison to the pathological results. The BI-RADS categories were scored on a scale from 1 to 5, and SWEmax, SWEratio, and SMI_VI were dichotomized based on each cutoff values (0 or 1). The combined scores (1 to 8) were calculated as the sum of the BI-RADS score and the quantitative scores and compared to the pathologic results using AUROC analysis. The cutoff values were 52.25 kPa for SWEmax, 5.03 for SWEratio, and 2.15% for SMI_VI. In AUROC, the combined scores showed significantly better diagnostic performance compared to BI-RADS alone (p < 0.001). The combined score showed significantly increased than BI-RADS alone in specificity (p < 0.001) and accuracy (p < 0.001), but a sensitivity decreased without significance (p = 0.082). When a combined score cutoff value of 4 was used, the false negative rate was 2.7%. Using the combined score, 76.4% of the C4a lesions were considered benign also pathologically diagnosed as benign. The combined scores showed improved diagnostic performance in differentiating between benign and malignant breast masses, which could be helpful for determining a breast biopsy eligibility.

Which combination of different ultrasonography modalities is more appropriate to diagnose breast cancer?: A network meta-analysis (a PRISMA-compliant article)

BACKGROUND

Abundant amount of literature that analyze the various detection of different ultrasound methods, no comprehensive literature that investigates the diagnostic values of breast cancer (BC) by different ultrasonography modalities through a network meta-analysis (NMA) has been made available. Each imaging diagnostic examination has its own advantages and disadvantages, and any imaging examination is not enough to make an accurate diagnosis of the disease. Thus, this study aimed to compare diagnostic values among different ultrasonography modalities, including the information of 2-dimension, stiffness and blood flow, by a network meta-analysis in the hopes of understanding which imaging methods are better and which combination of different ultrasonography modalities is more appropriate to diagnose BC.

METHODS

We made use of Cochrane Library, PubMed, and Embase in order to obtain literature and papers. The combination analysis of both direct and indirect evidence in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value(NPV) and accuracy was conducted so as to assess the odds ratios (ORs) and surface under the cumulative ranking curve (SUCRA) values of the 8 different ultrasound methods.

RESULTS

A total of 36 eligible diagnostic tests regarding 8 ultrasound methods were included in the study. According to this network meta-analysis, Breast Imaging Reporting and Data System (BI-RADS) 4b exhibited higher specificity, PPV, and accuracy and lower sensitivity and NPV than BI-RADS 4a. Contrast-enhanced ultrasound (CEUS) had the highest sensitivity, PPV, NPV and accuracy and superb microvascular imaging (SMI) had the highest specificity among color Doppler flow imaging (CDFI), power Doppler imaging(PDI), SMI and CEUS. There was no significant difference in diagnostic indexes between SMI and CEUS. Shear wave elastrography (SWE) had higher PPV and accuracy and lower sensitivity, specificity NPV than strain elastography (SE).

CONCLUSION

The results of this network meta-analysis suggested more appropriate combination of different ultrasound modalities is BI-RADS 4b, SMI, and SWE for the diagnosis of breast cancer.

Association Between Vascular Index Measured via Superb Microvascular Imaging and Molecular Subtype of Breast Cancer

Background

To determine whether vascular index (VI; defined as the ratio of Doppler signal pixels to pixels in the total lesion) measured via superb microvascular imaging in breast cancer correlates with immunohistochemically defined subtype and is able to predict molecular subtypes.

Methods

This prospective study involved 225 patients with 225 mass-type invasive breast cancers (mean size 2.6 ± 1.4 cm, range 0.4~5.9 cm) who underwent ultrasound and superb microvascular imaging (SMI) at Peking Union Medical College Hospital before breast surgery from December 2016 to June 2018. The correlations between primary tumor VI measured via SMI, clinicopathological findings, and molecular subtype were analyzed. The performance of VI for prediction of molecular subtypes in invasive breast cancer was investigated.

Results

The median VI of the 225 tumors was 7.3% (4.2%~11.8%) (range 0%~54.4%). Among the subtypes of the 225 tumors, 41 (18.2%) were luminal A, 91 (40.4%) were luminal B human epidermal growth factor receptor-2 (HER-2)-negative, 26 (11.6%) were luminal B HER-2-positive, 17 (7.6%) were HER-2-positive, and 50 (22.2%) were triple-negative, and the corresponding median VI values were 5.9% (2.6%~11.6%) (range 0%~47.1%), 7.3 (4.4%~10.5%) (range 0%~29.5%), 6.3% (3.9%~11.3%) (range 0.6%~22.2%), 8.2% (4.9%~15.6%) (range 0.9%~54.4%), and 9.2% (5.1%~15.3%) (range 0.7%~32.9%), respectively. Estrogen receptor (ER) negativity, higher tumor grade, and higher Ki-67 index (≥20%) were significantly associated with a higher VI value. Tumor size, ER status, and Ki-67 index were shown to independently influence VI. A cutoff value of 4.1% yielded 79.9% sensitivity and 41.5% specificity with an area under the receiver operating characteristic curve (AUC) of 0.58 for predicting that a tumor was of the luminal A subtype. A cutoff value of 16.4% yielded 30.0% sensitivity and 90.3% specificity with an AUC of 0.60 for predicting a triple-negative subtype.

Conclusions

VI, as a quantitative index obtained by SMI examination, could reflect histologic vascular changes in invasive breast cancer and was found to be higher in more biologically aggressive breast tumors. VI shows a certain degree of correlation with the molecular subtype of invasive breast cancer and plays a limited role in predicting the luminal A with high sensitivity and triple-negative subtype with high specificity.

The Updated Role of Transcranial Ultrasound Neuromodulation in Ischemic Stroke: From Clinical and Basic Research

Ischemic stroke is a common cause of death and disability worldwide, which leads to serious neurological and physical dysfunction and results in heavy economic and social burdens. For now, timely and effective dissolution of thrombus, and ultimately improvement in the recovery of neurological functions, is the treatment strategy focus. Recently, many studies have reported that transcranial ultrasound stimulation (TUS), as a non-invasive method, can dissolve thrombus, improve cerebral blood circulation, and exert a neuroprotective effect post-stroke. TUS can promote functional recovery and improve rehabilitation efficacy among patients with ischemic stroke. This mini-review summarizes the potential mechanism and limitation of TUS in stroke aims to provide a new strategy for the future treatment of patients with ischemic stroke.

The diagnostic value of contrast-enhanced ultrasound and superb microvascular imaging in differentiating benign from malignant solid breast lesions: A systematic review and meta-analysis

OBJECTIVE

To investigate the added value of contrast-enhanced ultrasound (CEUS) and superb microvascular imaging (SMI) to the conventional ultrasound (US) in the diagnosis of breast lesions.

METHODS

PubMed, EMBASE, Web of Science, Chinese national knowledge infrastructure databases, Chinese biomedical literature databases, and Wanfang were searched for relevant studies from November 2015 to November 2021. The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Studies (QUADAS) tool. Meta-Disc version 1.4 was used to calculate sensitivity (SEN), specificity (SPE), positive likelihood ratio (LR +), negative likelihood ratio (LR-), area under curve (AUC), and diagnostic odds ratio (DOR). Meta-regression analysis was performed using STATA 16.0 software to compare the diagnostic accuracy of the two techniques.

RESULTS

In the five studies included, 530 patients were eligible for this meta-analysis. For SMI, the pooled SEN and SPE were 0.75 (95% confidence interval [CI]: 0.69-0.91) and 0.88 (95% CI: 0.83-0.91), respectively, LR + was 5.75 (95% CI: 4.26-7.78), LR- was 0.29 (95% CI: 0.23-0.36), DOR was 21.42 (95% CI, 13.61-33.73), and AUC was 0.8871. For CEUS, the pooled SEN and SPE were 0.87 (95% CI: 0.82-0.91) and 0.86 (95% CI: 0.82-0.89), respectively, LR + was 5.92 (95% CI: 4.21-8.33), LR- was 0.16 (95% CI: 0.11-0.25), DOR was 38.27 (95% CI: 18.73-78.17), and AUC was 0.9210.

CONCLUSIONS

Adding CEUS and (or) SMI to conventional US could improve its diagnostic performance in differentiating benign from malignant solid breast lesions.

Quantification and Classification of Contrast Enhanced Ultrasound Breast Cancer Data: A Preliminary Study

This study aimed to investigate which of the two frequently adopted perfusion models better describes the contrast enhanced ultrasound (CEUS) perfusion signal in order to produce meaningful imaging markers with the goal of developing a machine-learning model that can classify perfusion curves as benign or malignant in breast cancer data. Twenty-five patients with high suspicion of breast cancer were analyzed with exponentially modified Gaussian (EMG) and gamma variate functions (GVF). The adjusted R² metric was the criterion for assessing model performance. Various classifiers were trained on the quantified perfusion curves in order to classify the curves as benign or malignant on a voxel basis. Sensitivity, specificity, geometric mean, and AUROC were the validation metrics. The best quantification model was EMG with an adjusted R² of 0.60 ± 0.26 compared to 0.56 ± 0.25 for GVF. Logistic regression was the classifier with the highest performance (sensitivity, specificity, G_mean, and AUROC = 89.2 ± 10.7, 70.0 ± 18.5, 77.1 ± 8.6, and 91.0 ± 6.6, respectively). This classification method obtained similar results that are consistent with the current literature. Breast cancer patients can benefit from early detection and characterization prior to biopsy.

Quantitative analysis of vascularity for thyroid nodules on ultrasound using superb microvascular imaging: Can nodular vascularity differentiate between malignant and benign thyroid nodules?

This study aimed to investigate the utility of adding superb microvascular imaging (SMI) to B-mode ultrasound (US) for distinguishing between benign and malignant thyroid nodules and evaluate the usefulness of SMI quantification of nodular vascularity for diagnosing thyroid cancer.The malignancy likelihood was scored for 3 datasets before versus after additional color Doppler imaging or SMI using 4-scale visual analysis (i.e., B-mode US alone, B-mode US + color Doppler image, and B-mode US + SMI). Further, the SMI pixel count was measured in the region of interest, including the whole nodule, on the longitudinal view. It was compared between benign and malignant nodules and analyzed according to the US patterns of thyroid nodules based on the Korean thyroid imaging reporting and data system. We calculated the area under the receiver operating characteristic curve values, sensitivities, and specificities.There was no significant difference in the area under the receiver operating characteristic curve values among B-mode, B-mode + color Doppler, and B-mode + SMI. However, the SMI pixel count was significantly higher in malignant thyroid nodules than in benign ones. The optimal cut-off value for the SMI pixel count for predicting malignant thyroid nodules obtained using a receiver operating characteristic curve was 17 (40.54% in sensitivity, 91.3% in specificity). Analysis based on the US pattern of thyroid nodules revealed significant differences in the nodules with low-to-intermediate suspicious US features between malignant and benign nodules.Quantification analysis of vascularity using SMI can differentiate malignant thyroid nodules from benign ones.

Seeing the unseen with superb microvascular imaging: Ultrasound depiction of normal dermis vessels

PURPOSE

Current color- and power-Doppler techniques cannot demonstrate vascularization of the dermis. Aim of this prospective study was to investigate whether the new superb vascular imaging (SMI) technique improves the ultrasound (US) depiction of dermis vessels in healthy volunteers. SMI was compared side-by-side to conventional power-Doppler (PD) imaging.

METHODS

Thirty adult subjects (18 men and 12 women, mean age 45 years old) were evaluated with US at level of five body areas: forehead, forearm, palm, buttock, and thigh. The vascular index (VI) was employed to objectively quantify the difference between SMI and PD imaging in terms of dermis flow amount.

RESULTS

Forehead VI was higher for SMI than for PD in 93% of cases, forearm VI was higher for SMI than for PD in 97% of cases, palm VI was higher for SMI than for PD in 87% of cases, buttock VI was higher for SMI than for PD in 100% of cases, thigh VI was higher for SMI than for PD in 100% of cases. SMI-detected vascular signals in 100% of the body areas. PD failed to show any flow signals from the forehead in 23% of cases, forearm in 37% of cases, palm in 33% of cases, buttock in 47% of cases, and thigh in 50% of cases.

CONCLUSION

SMI can demonstrate normal dermis vascularization whereas conventional PD cannot. SMI is a sensitive and promising technique in the study of dermis abnormalities, particularly when quantifying the disease activity is important.

Diagnostic value of various vascular features of breast cancer by age

BACKGROUND

Tumor angiogenesis plays a critical role in the growth and metastasis of breast cancer. Evaluating the added value of vascular features to Breast Imaging Reporting and Data System (BI-RADS) in differentiating malignant masses from benign ones is essential. Micro-flow Imaging (MFI) is a promising noninvasive diagnostic method for the microvessels in breast tumors, but its precise value is still uncertain.

OBJECTIVES

Understanding whether malignant tumor vascular characteristics by MFI are associated with breast cancer and whether the diagnostic efficiency varies by age.

MATERIALS AND METHODS

B-mode ultrasound and MFI were performed for 153 solid breast lesions. The vessels images by MFI were reviewed and assessed by two investigators, respectively. Then the diagnostic efficacy of different vascular features combined with BI-RADS was evaluated in different age groups.

RESULTS

The mean size of lesions is 19.4 (range 18-78) mm. There were 94 breast masses in benign, while 59 breast masses in malignant by pathology. III Adler classification, penetrating vessels, and complex flow pattern showed a positive association with a high risk of malignant breast lesions (p < 0.05). BI-RADS combined with vessel characteristics show better improvement of diagnostic performance of breast lesions in the elderly group than in the young group.

CONCLUSIONS

Vascular features by MFI contribute to malignant breast masses' diagnosis, and the association might be modified by age.

Combination of shear wave elastography and BI-RADS in identification of solid breast masses

BACKGROUND

To explore the value of quantitative shear wave elastography (SWE) plus the Breast Imaging Reporting and Data System (BI-RADS) in the identification of solid breast masses.

METHODS

A total of 108 patients with 120 solid breast masses admitted to our hospital from January 2019 to January 2020 were enrolled in this study. The pathological examination served as the gold standard for definitive diagnosis. Both SWE and BI-RADS grading were performed.

RESULTS

Out of the 120 solid breast masses in 108 patients, 75 benign and 45 malignant masses were pathologically confirmed. The size, shape, margin, internal echo, microcalcification, lateral acoustic shadow, and posterior acoustic enhancement of benign and malignant masses were significantly different (all P < 0.05). The E mean, E max, SD, and E ratio of benign and malignant masses were significantly different (all P < 0.05). The E min was similar between benign and malignant masses (P > 0.05). The percentage of Adler grade II-III of the benign masses was lower than that of the malignant masses (P < 0.05). BI-RADS plus SWE yielded higher diagnostic specificity and positive predictive value than either BI-RADS or SWE; BI-RADS plus SWE yielded the highest diagnostic accuracy among the three methods (all P < 0.05).

CONCLUSION

SWE plus routine ultrasonography BI-RADS has a higher value in differentiating benign from malignant breast masses than color doppler or SWE alone, which should be further promoted in clinical practice.

Ultrasound-Based Nomogram for Distinguishing Malignant Tumors from Nodular Sclerosing Adenoses in Solid Breast Lesions

OBJECTIVES

Nodular sclerosing adenoses (NSAs) and malignant tumors (MTs) may coexist and are often classified into the same Breast Imaging Reporting and Data System (BI-RADS) category. We aimed to build and validate an ultrasound-based nomogram to distinguish MT from NSA for building a precise sequence of biopsies.

MATERIALS AND METHODS

The training cohort included 156 patients (156 masses) with NSA or MT at one study institution. We used best subset regression to determine the predictors for building a nomogram from ultrasonic characteristics and patients' age. Model performance and clinical utility were evaluated using Brier score, concordance (C)-index, calibration curve, and decision curve analysis. The independent validation cohort consisted of 162 patients (162 masses) from a separate institution.

RESULTS

Through best subset regression, we selected 6 predictors to develop nomogram: age, calcification, echogenic rim, vascularity distribution, tumor size, and thickness of breast parenchyma. Brier score and C-index of the nomogram in the training cohort were 0.068 and 0.967 (95% confidence interval [CI]: 0.941-0.993), respectively. In addition, calibration curve demonstrated good agreement between prediction and pathological result. In the validation cohort, the nomogram still obtained a favorable C-index score of 0.951 (95% CI: 0.919-0.983) and fine calibration. Decision curve analysis showed that the model was clinically useful.

CONCLUSIONS

If multiple NSA and MT masses are present in the same patient and are classified into the same BI-RADS category, our nomogram can be used as a supplement to the BI-RADS category for accurate biopsy of the mass most likely to be MT.

Ultrasonographic Detection of Vascularity of Focal Breast Lesions: Microvascular Imaging Versus Conventional Color and Power Doppler Imaging

To compare microvascular flow imaging (MVFI) to conventional Color-Doppler (CDI) and Power-Doppler (PDI) imaging in the detection of vascularity of Focal Breast Lesions (FBLs). A total of 180 solid FBLs (size: 3.5-45.2 mm) detected in 180 women (age: 21-87 years) were evaluated by means of CDI, PDI, and MVFI. Two blinded reviewers categorized lesion vascularity in absent or present, and vascularity pattern as (a) internal; (b) vessels in rim; (c) combined. The presence of a "penetrating vessel" was assessed separately. Differences in vascularization patterns (chi² test) and intra- and inter-observer agreement (Fleiss method) were calculated. ROC analysis was performed to assess performance of each technique in differentiating benign from malignant lesions. About 103/180 (57.2%) FBLs were benign and 77/180 (42.8%) were malignant. A statistically significant (p < .001) increase in blood flow detection was observed for both readers with MVFI in comparison to either CDI or PDI. Benign FBLs showed mainly absence of vascularity (p = .02 and p = .01 for each reader, respectively), rim pattern (p < .001 for both readers) or combined pattern (p = .01 and p = .04). Malignant lesions showed a statistically significant higher prevalence of internal flow pattern (p < .001 for both readers). The prevalence of penetrating vessels was significantly higher with MVFI in comparison to either CDI or PDI (p < .001 for both readers) and in the malignant FBLs (p < .001). ROC analysis showed MVFI (AUC = 0.70, 95%CI = [0.64-0.77]) more accurate than CDI (AUC = 0.67, 95%CI = [0.60-0.74]) and PDI (AUC = 0.67, 95%CI = [0.60-0.74]) though not significantly (p = .5436). Sensitivity/Specificity values for MVFI, PDI, and CDI were 76.6%/64.1%, 59.7%/73.8% and 58.4%/74.8%, respectively. Inter-reader agreement with MVFI was always very good (k-score 0.85-0.96), whereas with CDI and PDI evaluation ranged from good to very good. No differences in intra-observer agreement were noted. MVFI showed a statistically significant increase in the detection of the vascularization of FBLs in comparison to Color and Power-Doppler.

Comparison of the Effectiveness of Shear Wave Elastography and Superb Microvascular Imaging in the Evaluation of Breast Masses

ABSTRACT

This study aims to determine the diagnostic performance of superb microvascular imaging (SMI) and shear wave elastography methods in evaluating breast lesions. We will also compare the effectiveness of the stiffness, velocity, and vascular index (VI) parameters in distinguishing malignancy.From January to June 2019, 121 patients with 121 solid breast masses (category 4 and 5 lesions according to the Breast Imaging-Reporting and Data System) detected during the routine grayscale sonographic examination were included in the study. Stiffness and velocity values were obtained using shear wave elastography for all lesions, and VI was obtained using SMI. The receiver operating characteristic curves were obtained to set the best cutoff values for the stiffness, velocity, and VI to differentiate patients with malignant breast lesions.All 121 lesions were pathologically verified by US-guided core needle biopsy. Forty-seven (38.9%) of the lesions were malignant, and 74 (61.1%) were benign. Median stiffness, velocity, and VI values were significantly lower in benign masses compared with malignant masses (P < 0.001). The optimum cutoff values for the stiffness, velocity, and VI were determined to be 58.3 kPa, 4.5 m/s, and 1.1%, respectively. The areas under the curves were 0.897 for stiffness, 0.884 for velocity, and 0.687 for VI.Shear wave elastography and SMI are noninvasive methods that may be used to evaluate breast masses. Although both methods' quantitative data are beneficial in differentiating malignant from benign masses, stiffness is the best parameter to be used.

Clinical Applications of Superb Microvascular Imaging in the Superficial Tissues and Organs: A Systematic Review

Superb microvascular imaging (SMI) is an innovative Doppler technique for vascular examination. It uses an intelligent algorithm that efficiently separates low-speed flow signals from motion artifacts so that it can assess microvessels and the vessel distribution in detail. This article reviews the clinical applications of SMI in the disorders of superficial tissues and organs including thyroid nodules, breast tumors and lymph node diseases etc. More information of diseases that are closely associated with angiogenesis can be shown by SMI than other noninvasive examinations. Although some limitations exist, this safe and convenient technique is becoming acceptable and would play a more important role in disease diagnosis and therapeutic responses evaluation.

Added Value of the Vascular Index on Superb Microvascular Imaging for the Evaluation of Breast Masses: Comparison With Grayscale Ultrasound

OBJECTIVES

To evaluate the value of the vascular index (VI) on Superb Microvascular Imaging (SMI; Canon Medical Systems Corporation, Tokyo, Japan) in comparison with grayscale ultrasound (US) alone for assessing breast masses.

METHODS

We evaluated a total of 70 breast masses (36 malignant and 34 benign lesions) in 70 consecutive patients using grayscale US and SMI. Two breast radiologists analyzed grayscale US alone and the combination of grayscale US and SMI. They also measured the VI based on SMI. The diagnostic performance of grayscale US alone and the combination of grayscale US and SMI was compared. The VI was compared between benign and malignant masses, and the optimal cutoff value was determined. In addition, the interobserver agreement in imaging analyses and the VI was assessed.

RESULTS

The interobserver agreements in imaging analyses and the VI were almost perfect. The VI of malignant breast masses was significantly higher than that of benign lesions (P < .001). The optimal cutoff value of the VI for differentiating between malignant and benign breast masses was 2.95, with sensitivity of 86.1% and specificity of 91.2%. The diagnostic performance values of grayscale US alone and the combination of grayscale US and SMI were 0.824 and 0.912, respectively, for reader 1 (P = .028) and 0.795 and 0.853 for reader 2 (P = .101).

CONCLUSIONS

The VI on SMI was significantly higher for malignant breast masses than for benign lesions, with high interobserver agreement. Our study suggests that the combination of grayscale US and SMI with the VI could improve the characterization of breast masses.

Breast Ultrasound Microvascular Imaging and Radiogenomics

Microvascular ultrasound (US) techniques are advanced Doppler techniques that provide high sensitivity and spatial resolution for detailed visualization of low-flow vessels. Microvascular US imaging can be applied to breast lesion evaluation with or without US contrast agents. Microvascular US imaging without a contrast agent uses a sophisticated wall filtering system to selectively obtain low-flow Doppler signals from overlapped artifacts. Microvascular US imaging with second-generation contrast agents amplifies flow signals and makes them last longer, which facilitates hemodynamic evaluation of breast lesions. In this review article, we will introduce various microvascular US techniques, explain their clinical applications in breast cancer diagnosis and radiologic-histopathologic correlation, and provide a summary of a recent radiogenomic study using microvascular US.

Assessment of Additional MRI-Detected Breast Lesions Using the Quantitative Analysis of Contrast-Enhanced Ultrasound Scans and Its Comparability with Dynamic Contrast-Enhanced MRI Findings of the Breast

Purpose

To assess the diagnostic performance of contrast-enhanced ultrasound (CEUS) for additional MR-detected enhancing lesions and to determine whether or not kinetic pattern results comparable to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast can be obtained using the quantitative analysis of CEUS.

Materials and Methods

In this single-center prospective study, a total of 71 additional MR-detected breast lesions were included. CEUS examination was performed, and lesions were categorized according to the Breast Imaging-Reporting and Data System (BI-RADS). The sensitivity, specificity, and diagnostic accuracy of CEUS were calculated by comparing the BI-RADS category to the final pathology results. The degree of agreement between CEUS and DCE-MRI kinetic patterns was evaluated using weighted kappa.

Results

On CEUS, 46 lesions were assigned as BI-RADS category 4B, 4C, or 5, while 25 lesions category 3 or 4A. The diagnostic performance of CEUS for enhancing lesions on DCE-MRI was excellent, with 84.9% sensitivity, 94.4% specificity, and 97.8% positive predictive value. A total of 57/71 (80%) lesions had correlating kinetic patterns and showed good agreement (weighted kappa = 0.66) between CEUS and DCE-MRI. Benign lesions showed excellent agreement (weighted kappa = 0.84), and invasive ductal carcinoma (IDC) showed good agreement (weighted kappa = 0.69).

Conclusion

The diagnostic performance of CEUS for additional MR-detected breast lesions was excellent. Accurate kinetic pattern assessment, fairly comparable to DCE-MRI, can be obtained for benign and IDC lesions using CEUS.

Modified Model for Diagnosing Breast Imaging Reporting and Data System Category 3 to 5 Breast Lesions: Retrospective Analysis and Nomogram Development

OBJECTIVES

The aim of this study was to explore a modified model to simplify the diagnostic process for American College of Radiology Breast Imaging Reporting and Data System category 3 to 5 breast lesions and evaluate the model's diagnostic efficacy.

METHODS

A retrospective review was conducted of breast lesions examined by B-mode ultrasound (US) and contrast-enhanced ultrasound (CEUS) and diagnosed by histopathologic examination from October 2016 to August 2019. The US characteristics of a combined model (US + CEUS model) with relatively high diagnostic value were selected by a lasso regression analysis to establish a modified model. Two nomograms were developed. The results were internally validated by bootstrap resampling.

RESULTS

Overall, 206 breast lesions in 198 patients, 136 benign and 70 malignant, were included. Ultrasound characteristics included in the modified model were shape, margin, microcalcification, enhanced intensity, enhanced scope, and enhanced time. For the US + CEUS model and modified model, sensitivities were 94.3% and 93.3%; specificities were 85.9% and 81.4%; accuracies were 89.3% and 88.7% and areas under the curve were 0.957 and 0.944, respectively. No statistically significant differences were seen in the diagnostic efficacies of the models (P = .097). Bootstrap-corrected sensitivities, specificities. and accuracies of the models were consistent with these results. Bootstrap-corrected areas under the curve for the US + CEUS model and the modified model were 0.955 and 0.940, respectively.

CONCLUSIONS

The modified model with fewer indicators conveniently and effectively diagnosed the malignancy of Breast Imaging Reporting and Data System category 3 to 5 breast lesions without reducing diagnostic efficacy.

Diagnostic Value of Contrast-Enhanced Ultrasonography With SonoVue in the Differentiation of Benign and Malignant Breast Lesions: A Meta-Analysis

PURPOSE

A meta-analysis was conducted to evaluate the diagnostic performance of contrast-enhanced ultrasonography using the contrast agent SonoVue to differentiate benign from malignant breast lesions.

METHOD

A comprehensive search of the literature was performed using the Embase, PubMed, and Web of Science databases to retrieve studies published before February 2020. Data were extracted, and pooled sensitivity, specificity, and diagnostic odds ratios were calculated with meta-analysis software. Heterogeneity was evaluated via the Q test and I² statistic. Meta-regression and subgroup analyses were applied to evaluate potential sources of heterogeneity. Publication bias was assessed using the Deeks' funnel plot asymmetry test. A summary receiver operating characteristic curve (SROC) was constructed.

RESULTS

A total of 27 studies including 5378 breast lesions subjected to CEUS examination with SonoVue were included in the meta-analysis. The pooled sensitivity and specificity values were 0.90 (95% confidence interval [CI], 0.88-0.91; inconsistency index [I²] = 75.7%) and 0.83 (95% CI, 0.82-0.85; I² = 91.0%), respectively. The pooled diagnostic odds ratio was 48.35% (95% CI, 31.22-74.89; I² = 77.6%). The area under the summary receiver operating characteristic curve (AUC) was 0.9354. Meta-regression analysis revealed the region of patient residence and dose of contrast agent as potential sources of heterogeneity (P < .01). Subgroup analysis showed a higher area under the summary receiver operating characteristic curve for European and higher contrast agent dose subgroups (P < .05).

CONCLUSION

Contrast-enhanced ultrasonography with SonoVue displays high sensitivity, specificity, and accuracy when differentiating benign from malignant breast lesions. Despite its current limitations, this technique presents a promising tool for diagnosing breast lesions in clinical practice.

Combination of Quantitative Parameters of Shear Wave Elastography and Superb Microvascular Imaging to Evaluate Breast Masses

Objective

This study aimed to evaluate the diagnostic value of combining the quantitative parameters of shear wave elastography (SWE) and superb microvascular imaging (SMI) to breast ultrasound (US) to differentiate between benign and malignant breast masses.

Materials and Methods

A total of 200 pathologically confirmed breast lesions in 192 patients were retrospectively reviewed using breast US with B-mode imaging, SWE, and SMI. Breast masses were assessed based on the breast imaging reporting and data system (BI-RADS) and quantitative parameters using the maximum elasticity (Emax) and ratio (Eratio) in SWE and the vascular index in SMI (SMI_VI). The area under the receiver operating characteristic curve (AUC) value, sensitivity, specificity, accuracy, negative predictive value, and positive predictive value of B-mode alone versus the combination of B-mode US with SWE or SMI of both parameters in differentiating between benign and malignant breast masses was compared, respectively. Hypothetical performances of selective downgrading of BI-RADS category 4a (set 1) and both upgrading of category 3 and downgrading of category 4a (set 2) were calculated.

Results

Emax with a cutoff value of 86.45 kPa had the highest AUC value compared to Eratio of 3.57 or SMI_VI of 3.35%. In set 1, the combination of B-mode with Emax or SMI_VI had a significantly higher AUC value (0.829 and 0.778, respectively) than B-mode alone (0.719) (p < 0.001 and p = 0.047, respectively). B-mode US with the addition of Emax, Eratio, and SMI_VI had the best diagnostic performance of AUC value (0.849). The accuracy and specificity increased significantly from 68.0% to 84.0% (p < 0.001) and from 46.1% to 79.1% (p < 0.001), respectively, and the sensitivity decreased from 97.6% to 90.6% without statistical loss (p = 0.199).

Conclusion

Combining all quantitative values of SWE and SMI with B-mode US improved the diagnostic performance in differentiating between benign and malignant breast lesions.

Reproducibility and diagnostic performance of the vascular index of superb microvascular imaging in real-time breast ultrasonography for evaluating breast masses

Purpose

This study aimed to evaluate the reproducibility and diagnostic performance of a quantitative parameter of superb microvascular imaging (SMI) in real-time breast ultrasonography (US) for differentiating benign from malignant breast masses.

Methods

Eighty-seven breast masses in 75 patients who underwent both B-mode US and SMI before US-guided core needle biopsy were included in this study. Two radiologists performed B-mode US and measured the vascular index (VI) of SMI respectively for each lesion in real time. Intraobserver and interobserver agreements were analyzed for the VI of SMI. The diagnostic performance of B-mode US using the Breast Imaging Reporting and Database System lexicon and combined use with the VI of SMI was evaluated compared to pathology.

Results

The median VI of malignant masses (n=32) was significantly higher than that of benign masses (n=55) (7.6% and 2.6%, respectively; P<0.001). The intraobserver agreement for VI was excellent regardless of the pathology, size, or depth of the lesion. The interobserver agreement for VI was excellent regardless of the presence of a measurement interval. The interobserver agreement for the final diagnostic decision was improved by combining B-mode US and VI (κ=0.883) in comparison with B-mode US only (κ=0.617). Adding VI led to significant improvements in the specificity (87.2% vs. 52.7%, 83.6% vs. 49.0%), accuracy (89.7% vs. 69.3%, 84.0% vs. 65.9%) and positive predictive value (81.5% vs. 55.1%, 75.6% vs. 52.6%) of B-mode US for both observers compared with B-mode US alone (all, P=0.001).

Conclusion

The VI of SMI for real-time breast US is highly reproducible and leads to improved diagnostic performance for differentiating between benign and malignant breast lesions in combination with B-mode US.

Efficacy of superb microvascular imaging of ultrasound for diagnosis of gallbladder lesion

BACKGROUND/PURPOSE

The diagnosis of gallbladder (GB) lesions is occasionally difficult. Recently, superb microvascular imaging (SMI) of ultrasound has been developed as a novel microvascular imaging technique. We evaluated the feasibility of SMI for the diagnosis of GB lesions and compared microvascular imaging between benign and malignant GB lesions.

METHODS

Twenty patients with GB-protruded lesions or wall thickening who underwent SMI from August 2015 to July 2017 were included in this retrospective study. The measured outcomes were the quality of microvascular imaging when compared between normal SMI (N-SMI) and contrast-enhanced SMI (CE-SMI), and the microvascular findings (vascularity, vascular morphology, presence of branching, and presence of caliber change) when compared between benign and malignant GB lesions.

RESULTS

The quality of microvascular imaging of CE-SMI was evaluated as better than that of N-SMI, showing a significant difference (P < .001). From the CE-SMI microvascular findings, the evaluation of vascular morphology and the presence of caliber change showed a significant difference between benign and malignant GB lesions (P = .005, P < .001).

CONCLUSIONS

The evaluation of GB lesions using SMI was feasible with a contrast agent. Vascular morphology and the presence of caliber change may help in the differential diagnosis of GB lesions.